Detecting and quantifying patient motion during tomosynthesis scans

ABSTRACT

The effects of patient motion in tomosynthesis scan images are automatically detected and quantified. In at least one embodiment an indication of detection of the effects of patient motion in tomosynthesis scan images is provided shortly after the scan, e.g., before the patient is discharged or before the breast is decompressed. A patient motion score may be calculated as part of motion quantification. The score may be stored for subsequent retrieval. Images may be presented with reference features to help a technician confirm of the effects of motion in images.

CROSS-REFERENCE TO RELATED APPLICATIONS

A claim of priority is made to United States Provisional PatentApplication Ser. No. 61/370485, filed Aug. 4, 2010, entitled SYSTEM ANDMETHOD FOR DETECTING PATIENT MOTION DURING TOMOSYNTHESIS SCANS, which isincorporated by reference.

BACKGROUND

X-ray screening exams are used to detect breast cancer and otherdiseases. Efforts to improve the sensitivity and specificity of breastx-ray systems have lead to the development of tomosynthesis systems.Breast tomosynthesis is a three-dimensional imaging technology thatinvolves acquiring images of a stationary compressed breast at multipleangles during a short scan. The individual images are reconstructed intoa series of thin, high-resolution slices that can be displayedindividually or in a dynamic ciné mode. Reconstructed tomosynthesisslices reduce or eliminate the problems caused by tissue overlap andstructure noise in single slice two-dimensional mammography imaging.Digital breast tomosynthesis also offers the possibility of reducedbreast compression, improved diagnostic and screening accuracy, fewerrecalls, and 3D lesion localization. Examples of breast tomosynthesissystems are described in U.S. Pat. Nos. 7,245,694 and 7,123,684,commonly owned by the Assignee of this application.

In order to facilitate screening and diagnosis with tomosynthesissystems it is generally desirable to obtain high quality images. Onecause of degradation of image quality is patient motion during thetomosynthesis scan. Patient motion tends to cause blurring of one ormore of the images. The blurring can be severe enough to render theassociated images unacceptable for clinical screening or diagnosis.Further complicating the problem, the tomosynthesis images obtainedduring a scan might not be analyzed until after the patient's breast hasbeen decompressed and the patient has been discharged. As a result, thepatient must be called back for a new scan due to severe image blurring,thereby increasing patient frustration and anxiety, and potentiallydelaying diagnosis of malignancies.

SUMMARY

In accordance with one aspect of the invention an apparatus comprises:an image acquisition mechanism that generates a plurality of images ofan imaging target in a time series during a scan; an image processorthat processes the images; a computer which detects motion of the targetduring the scan by comparing an actual location of at least one point ofreference in each individual processed image with an expected locationof the at least one point of reference derived from a set of theprocessed images; and a mechanism for prompting a responsive action ifmotion is detected.

In accordance with another embodiment of the invention a methodcomprises: generating a plurality of images of an imaging target in atime series during a scan; processing the images; using a computer,detecting motion of the target during the scan by comparing an actuallocation of at least one point of reference in each individual processedimage with an expected location of the at least one point of referencederived from a set of the processed images; and prompting a responsiveaction if motion is detected.

Timely automatic detection and quantification of patient motion canprompt a screening technician to repeat a compromised scan beforepatient is discharged, or even before the breast is decompressed. Thisadvantageously mitigates patient frustration and anxiety, and alsoreduces diagnostic delays. Moreover, the results can be used to enhanceimage processing. These and other features and advantages will be morecompletely understood in light of the detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 a illustrates use of a feature to detect patient motion.

FIG. 1 b illustrates projection of a feature that is not affected bypatient movement.

FIG. 1 c illustrates projection of a feature that is affected by patientmovement.

FIG. 2 a illustrates use of an edge line feature to detect patientmotion.

FIG. 2 b illustrates projection of an edge line that is not affected bypatient movement.

FIG. 2 c illustrates projection of an edge line that is affected bypatient movement.

FIG. 3 illustrates displacement of selected locations of the series ofbreast skin line images.

FIG. 4 illustrates a 2^(nd) order curve fitted to the selectedlocations.

FIG. 5 illustrates a plot of maximum deviations at two segments oflocations along the compressed breast edge in a case of relativelysevere breast motion.

FIG. 6 illustrates a plot of maximum deviations at two segments oflocations along the compressed breast edge in a case of relativelyminimal breast motion.

FIG. 7 illustrates a method for detecting and quantifying patient motionduring a tomosynthesis scan.

FIGS. 8 a and 8 b illustrates a system capable of providing anindication to the technician if the motion score exceeds a predeterminedthreshold.

FIG. 9 illustrates presentation of images with reference features tohelp a technician confirm of the effects of motion in images.

DETAILED DESCRIPTION

One embodiment of the invention includes automatically detecting theeffects of patient motion in time-series scan images, e.g.,tomosynthesis images. Another embodiment of the invention includesproviding an indication of detection of the effects of patient motion intomosynthesis scan images, possibly shortly after the scan, e.g., beforethe patient is discharged or before the breast is decompressed. Anotherembodiment of the invention includes calculating a patient motion score.Another embodiment of the invention includes presenting images withreference features to help a technician confirm of the effects of motionin images. These and other embodiments of the invention are described ingreater detail below.

Baorui Ren et al., “Automatic patient motion detection in digital breasttomosynthesis,” Medical Imaging 2011: Physics of Medical Imaging, Proc.of SPIE Vol. 7961 7961 5F, (2011) is incorporated by reference.

Referring to FIG. 1 a, during a tomosynthesis scan a patient's breast102 is immobilized between a compression paddle 104 and a breastplatform 106. An x-ray receptor 110 is disposed within a housing locatedbelow the breast platform 106. An x-ray source 100 moves along an arc101 which may be centered on the top surface of the receptor 110. Atpredetermined discrete positions source 100 is energized to emit acollimated x-ray beam, for example and without limitation, at every1.07° of an arc of +/−7.5°. The beam irradiates the breast 102, andradiation that has passed through the breast is received by receptor110. Receptor 110 and associated electronics generate image data indigital form for each pixel of a rectangular grid of pixels at eachpredetermined discrete angular position of source 100.

The motion of source 100 can be continuous or discontinuous. If motionis continuous, a respective set of image data is accumulated over asmall increment of continuous motion, e.g., a 0.1° to 0.5° arc of motionof source 100, although these non-limiting parameters are only anexample. Different ranges of motion of the source 100 can be used, andthe motion of the source 100 may be along an arc centered at a differentaxis, such as inside immobilized breast 102 or at breast platform 106 orat receptor 110. Furthermore, source motion is not necessarily along anarc, and can be translational or a combination of different types ofmotions, such as partly translational and partly rotational.

Referring to FIGS. 1 a and 1 b, a distinct feature 103 of the breastwill project onto the detector at a different position for eachdifferent image, resulting in a projection path 20, because the x-raysource position is different for each image. Furthermore, a projectionpath 21 among all view angles generally follows a smooth trajectory fora tomosynthesis scan which is free of patient motion because of the wayx-ray source motion is defined, e.g., in a controlled arc, and becausex-ray exposures are taken in a temporally and spatially uniform manner.However, the projection of the feature will not follow a smoothtrajectory if the patient moves during the scan.

FIG. 1 c illustrates a projection path 22 where an image is affected bypatient movement. In one image the actual position 23 of the featurediffers from the expected position 24 of the feature. The differencebetween the actual position 23 and the expected position 24 isindicative of the magnitude of patient motion. Consequently, featuressuch as introduced markers, lesions, calcifications, masses and otherartifacts in or on the x-rayed object can be used to detect patientmotion and calculate an indication of the magnitude (severity) of themotion, e.g., using a computer with processors, non-transitory memoryand a computer program product which receives various inputs, performsvarious calculations, and provides outputs such as described in thisapplication.

Referring to FIGS. 2 a, 2 b, 2 c and 3, patient motion can also bedetected in a series of images based on displacement of an edge linesuch as the skin line of the breast, an implant edge, or some otherinternal edge. In order to utilize an edge line such as skin line 203 todetect motion, locations along the edge line are selected, e.g., fivepoints at each side of the nipple in a projection image. Location 200 isan example, but it should be noted that the present invention is notlimited to any particular number or arrangement of locations. Thelocations can be selected in one image and then used to calculatepositions of the corresponding locations in other images. For example, aline 300 which intersects a location 202 and is orthogonal to the skinline in a first image will intersect the skin line of a second image atthe first location of the second image. A non-orthogonal line 302 couldalternatively be used. The relative displacement of the locationsbetween N skin lines associated with N projection images is calculated,e.g., along the normal direction of the skin line at each location. FIG.2 b illustrates projection of an edge line that is not affected bypatient movement, as indicated by coincidence of expected and actualpositions of the selected location along the edge line. FIG. 2 cillustrates projection of an edge line that is affected by patientmovement, as indicated by displacement (motion amount) between theexpected position of the selected location and the actual position ofthe selected location in one image.

Some displacement is expected due to motion of the x-ray source.However, the rate of change of displacement should define a smooth curvein the absence of patient motion. Consequently, the rate of change ofdisplacement can also be used to detect patient motion.

Referring to FIG. 4, one way to detect the presence of patient motionand calculate the magnitude of that motion is to fit a 2^(nd) ordercurve to the locations/features of each image. The deviation of eachlocation/feature from the expected location on the 2^(nd) orderpolynomial fitting curve is then calculated. The maximum deviation isrecorded as the motion amount of the feature or skin line at theanalysis location. An example of severe breast motion is shown in FIG.5, where the magnitude of motion 500 is superimposed over the edge lines502 from which the magnitude is calculated. The horizontal axis of thegraph is the pixel location of skin lines along the chest wall directionof patient, while the vertical axis is the motion distance in unit ofmicron and in unit of number of detector pixel. It can be seen that themotion is greater on one side of the breast, in this example on the sidewith pixel locations <1000. An example with minimal motion is shown inFIG. 6.

The severity of patient motion may be used to automatically calculate amotion score. The motion score can be correlated to the displacementamount in selected units, e.g., in mm, where the displacement is thedeviation of the feature from the expected position or of the skin linepositions from the smooth curve. The maximum deviation of the curve isrecorded as the breast motion amount, or displacement, at the sampledlocation. The motion score may then be calculated by averaging theabsolute values of the displacement amounts across the projectionimages, taking a maximum displacement amount for any point along theproject path, or with various other techniques of using the displacementamounts to determine a motion score. Such techniques will be readilyapparent to those skilled in the art.

Referring to FIG. 7, a method of detecting and quantifying patientmotion begins with a scan 900 in which multiple images are obtained intime-series. The images are then transformed, reconstructed or otherwiseprocessed to generate one or more images that can be utilized to detectmotion as indicated by step 901. The result may be, for example, thesame or a different number of projection images or reconstructed slices.The next step 902 is to identify a reference feature or reference pointson an edge line associated with the breast. The actual locations of thefeatures/edge line reference points associated with N images of thebreast are then calculated in step 904. The expected locations of thefeatures/edge line reference points associated with the N images of thebreast are then calculated in step 906. The step can include, forexample, fitting a 2^(nd) order (or other order) curve to thefeatures/edge line reference points of all or a subset of images.Furthermore, the process may be iterative. For example, the number ofimages in the subset may be changed in different iterations. Also,different fitting models may be utilized in different iterations.Iteration may be stopped when predetermined conditions are satisfied.The deviation of each feature/edge line reference point from theexpected location is then calculated in step 908. The maximum deviationis recorded as the motion amount of the feature or skin line at theanalysis location in step 910. The process then continues with anotherqualified feature/edge line location, until multiple features/edge linelocations have been processed in order to analyze the entire breastvolume/skin line for motion. The motion score of the entire breast maythen be calculated in step 912. The entire algorithm for calculating themotion score is identified as group 950.

Referring to FIGS. 8 a and 8 b, an indication is provided to thetechnician if the motion score exceeds a predetermined threshold. Thescan 900 is followed by the Motion Calculator 950. The motion score 912is compared to a predefined threshold, and if exceeded, the motion scoreis stored in step 965 and a display or other indication 1003 ispresented to the user in step 975. The motion score may be stored in oneor more of various formats for subsequent retrieval. There are a varietyof Picture Archiving and Communication Systems (PACS) which storeimages. It is envisioned that PACS could store patient data includingmotion score in a non-transitory computer-readable memory. The motionindicator provided to the technician may include displaying a signal,icon, numerical score or other visual or auditory representation ofpatient motion on a user interface of the tomosynthesis system, e.g., onthe gantry 1000 or on a workstation 1002 coupled to the gantry forviewing by a radiologist. The indicator may simply indicate that thethreshold has been reached. Alternatively, the indicator may conveyseverity of motion to the technician, e.g., using a numerical score or awatermark, varying an intensity of a visual indicator, etc., to enablethe technician to selectively obtain an additional scan depending uponthe degree of potential image degradation based on patient motion. Inaddition, the indicator, or motion score, may be stored in a dicomheader or other field of patient data, saved to a database, and used byimage processing tools such as a Computer Assisted Detection system withmotion score incorporated and CAD decision optimized because of it (CADapplication).

Detection of patient motion and severity may be used to enhance thetomosynthesis system by prompting action by the operator. For example,in response to an exceeded threshold, the technician may immediatelyre-take the tomosynthesis images, perhaps before the patient isdismissed. A scan may be deemed acceptable by the operator if the motionscore is below the threshold, although some amount of patient motion hasbeen detected. The operator may also manually select images for removalfrom processing and reconstruction to improve the image quality of finalreconstruction slices. The motion detection can take place in real time,or at some later time after the patient has left or the operator isfinished with the procedure.

Motion analysis may also be used to automatically adjust or dispose ofimages most affected by patient motion. For example, if a subset of theimages exhibit motion, image reconstruction might be performed withoutthat subset of images that have been affected by motion, or performedwith all images after correction has been applied to the affected subsetof images. Such motion-score based processing may include proper globaland local adjustment, transformation, and, shift back to correct themotion amount. In addition, motion scores could be used to prompt andperform filtering to suppress the high-frequency content (edges, calcs)to prevent contamination (blurring) of the final image while passing thelow frequency content to improve the signal to noise ratio of finalimages.

Referring to FIG. 9, a set of images may be presented on the userinterface to enable the technician to confirm the presence of patientmotion. For example, the images may be presented in ciné mode withstationary reference lines or other features superimposed over theimages on the display monitor. The reference lines or featuresfacilitate visual confirmation of motion. For example, the distancebetween a nearby reference line and a distinct feature of the image maybe seen to change in ciné mode. Motion is indicated in the second imageof the three successive images in FIG. 9 by intersection of the skinline 1100 with the reference line 1102, and also by traversal ofreference line 1106 by lesion 1104. In practice it may be desirable tosuperimpose multiple parallel reference lines oriented with respect tothe breast image such that the reference lines are orthogonal to thedirection is most likely patient motion.

It is envisioned that motion detection and quantification may beperformed using reconstructed slice images although the above methods oftracking artifacts have described comparison of sequential projectionimages. In tomosynthesis reconstruction the projections images aresummed after shifting and transforming one relative to another in aspecific way (referred as component images) to produce a reconstructionslice that reinforces the spiculated lesion object located at the heightof that slice in a breast and reduces the contrast of other objectslocated away from the slice by blurring them out. One technique forperforming motion detection and quantification using reconstructed sliceimages is to compare individual locations in the component images withthe reconstructed slice image at the height at which the feature is infocus. The difference between locations in each individual componentimage versus the location in the reconstruction slice is used as thedisplacement in the calculations described above. Another example is toutilize a slice where the selected feature is out of focus. In such acase the locations of the selected feature appears as a trajectorycluster (epi-polar curve), so the analysis is performed by finding thelocation of each member of the cluster individually, and then findingthe expected location of that member. Accordingly the visualconfirmation method depicted in FIG. 9 can also be applied to reviewtomosynthesis reconstruction slices by co-displaying reference linessuperimposed on display monitor. Such alternative embodiments aretherefore within the scope of the present invention. Furthermore,although the above description has dealt largely with detecting patientmotion during tomosynthesis imaging for the purpose of predicting imagequality, it can easily be appreciated how the principles of the presentinvention may be extended beyond the tomosynthesis modality to anyimaging modality which acquires at least two images of an object over anextended time period. Such modalities include, but are not limited to,Computed Tomography (CT) scans, Positron Emission Tomography (PET)scans, Single Photon Emission Computed Tomography (SPECT) scans,ultrasound image acquisition, contrast enhanced imaging, and MagneticResonance Imaging (MRI). Thus, the present invention may be used for anytime-series of image acquisition system to identify any abnormal changesbetween sequenced images attributable to patient motion during theacquisition. Motion detection and analysis can also be included as partof system QC test; if mechanical component is malfunctioning, it wouldgenerate a non-zero motion score from phantom scan and help identify theproblem in the mechanical system.

Accordingly, a system, apparatus, method and computer program have beendescribed for detecting and quantifying motion of an object or acomponent of the motion of the object by evaluating displacement of afeature within a series of images acquired over a time period. Thefeature may be, without limitation, a skin line, internal edge line,internal object such as calcification, lesion, mass or other object, oran external marker. Any one of a variety of imaging modalities may beused, and the quantified motion may be displayed in any variety ofmanners, including but not limited to on the acquisition device, ontechnologist workstation, and in a dicom header. The quantified motionmay be used to generate a motion score, prompt re-acquisition of images,as an input to an image processing stage of a reconstruction algorithm,and as an input to a CAD processing system.

While the invention is described through the above exemplaryembodiments, it will be understood by those of ordinary skill in the artthat modification to and variation of the illustrated embodiments may bemade without departing from the inventive concepts herein disclosed.Moreover, while the preferred embodiments are described in connectionwith various illustrative structures, one skilled in the art willrecognize that the system may be embodied using a variety of specificstructures. Accordingly, the invention should not be viewed as limitedexcept by the scope and spirit of the appended claims.

1. Apparatus comprising: an image acquisition mechanism that generates aplurality of images of an imaging target in a time series during a scan;an image processor that processes the images; a computer which detectsmotion of the target during the scan by comparing an actual location ofat least one point of reference in each individual processed image withan expected location of the at least one point of reference derived froma set of the processed images; and a mechanism for prompting aresponsive action if motion is detected.
 2. The apparatus of claim 1wherein the at least one point of reference includes one or more of alesion, calcification, mass, skin line, external marker, internal edgeline or other object.
 3. The apparatus of claim 1 wherein the imageprocessor enhances the image or generates a mathematically transformedprojection image.
 4. The apparatus of claim 1 wherein the imageprocessor generates reconstructed slices.
 5. The apparatus of claim 1wherein the computer estimates the expected locations of the at leastone reference point in successive images.
 6. The apparatus of claim 5wherein the computer calculates the expected locations by fitting acurve to each reference point location or by averaging.
 7. The apparatusof claim 6 wherein the computer quantifies motion based on displacementof the reference point from the expected location.
 8. The apparatus ofclaim 7 wherein the computer quantifies motion based on maximumdisplacement of the reference point.
 9. The apparatus of claim 1 whereinthe computer calculates displacement of the at least one reference pointbetween N skin lines associated with N images along a selected directionrelative to the skin line.
 10. The apparatus of claim 9 wherein thecomputer quantifies motion based on change of displacement or rate ofchange of displacement of the at least one reference point.
 11. Theapparatus of claim 10 wherein the computer quantifies motion based onmaximum displacement of the reference point.
 12. The apparatus of claim1 wherein the computer calculates a motion score.
 13. The apparatus ofclaim 12 wherein the motion score is calculated using weighted average,max, median, min, or other operation.
 14. The apparatus of claim 12wherein an indication is provided to a technician if the motion scoreexceeds a predetermined threshold.
 15. The apparatus of claim 14 whereinthe indication includes at least one of a signal, icon, numerical scoreor other visual or auditory representation of patient motion displayedon a user interface of a gantry or workstation.
 16. The apparatus ofclaim 14 wherein the indication is stored in a dicom header or otherfield of patient data.
 17. The apparatus of claim 1 wherein theresponsive action includes automatically adjusting or disposing of animage.
 18. The apparatus of claim 1 wherein a set of images is presentedon an interface with at least one reference feature to enableconfirmation of motion.
 19. The apparatus of claim 1 wherein thecomputer selectively discards or mathematically corrects a portion ofprojection data during image reconstruction.
 20. The apparatus of claim1 wherein the image acquisition mechanism is selected from a group ofimage acquisition systems which acquire images using tomosynthesis, aComputed Technology (CT) image acquisition system, a PET, SPECT,Ultrasound, Contrast Enhanced, and MRI.
 21. A method comprising:generating a plurality of images of an imaging target in a time seriesduring a scan; processing the images; using a computer, detecting motionof the target during the scan by comparing an actual location of atleast one point of reference in each individual processed image with anexpected location of the at least one point of reference derived from aset of the processed images; and prompting a responsive action if motionis detected.
 22. The method of claim 21 including utilizing one or moreof a lesion, calcification, mass, skin line, external marker, internaledge line or other object as the point of reference.
 23. The method ofclaim 21 including enhancing the image or generating a mathematicallytransformed projection image.
 24. The method of claim 21 includinggenerating reconstructed slices.
 25. The method of claim 21 includingestimating the expected locations of the at least one reference point insuccessive images.
 26. The method of claim 25 including calculating theexpected locations by fitting a curve to each reference point locationor by averaging.
 27. The method of claim 26 including quantifying motionbased on displacement of the reference point from the expected location.28. The method of claim 27 including quantifying motion based on maximumdisplacement of the reference point.
 29. The method of claim 21including calculating displacement of the at least one reference pointbetween N skin lines associated with N images along a selected directionrelative to the skin line.
 30. The method of claim 29 includingquantifying motion based on change of displacement or rate of change ofdisplacement of the at least one reference point.
 31. The method ofclaim 30 including quantifying motion based on maximum displacement ofthe reference point.
 32. The method of claim 21 including calculating amotion score.
 33. The method of claim 32 including calculating themotion score using weighted average, max, median, min, or otheroperation.
 34. The method of claim 32 including providing an indicationto a technician if the motion score exceeds a predetermined threshold.35. The method of claim 34 including providing an indication with atleast one of a signal, icon, numerical score or other visual or auditoryrepresentation of patient motion displayed on a user interface of agantry or workstation.
 36. The method of claim 34 including storing theindication in a dicom header or other field of patient data.
 37. Themethod of claim 21 including automatically adjusting or disposing of animage as a responsive action.
 38. The method of claim 21 includingpresenting a set of images on an interface with at least one referencefeature to enable confirmation of motion.
 39. The method of claim 21including selectively discarding or mathematically correcting a portionof projection data during image reconstruction.
 40. The method of claim21 including generating the images using an image acquisition mechanismselected from a group of image acquisition systems which acquire imagesusing tomosynthesis, a Computed Technology (CT) image acquisitionsystem, a PET, SPECT, Ultrasound, Contrast Enhanced, and MRI.
 41. Themethod of claim 1 including storing information indicative of patientmotion.
 42. Apparatus comprising: a breast tomosynthesis system whichacquires a plurality of images of an imaging target in a time seriesduring a scan, processes the images, detects patient motion, andidentifies to a user that motion was detected.
 43. A method comprising:with a breast tomosynthesis system, acquiring a plurality of images ofan imaging target in a time series during a scan; processing the images;detecting patient motion; and identifying to a user that motion wasdetected.
 44. The method of claim 43 including storing informationindicative of patient motion.
 45. Apparatus comprising: a breasttomosynthesis system which acquires data, detects patient motion fromthe acquired data, and identifies to a user that motion was detected.46. A method comprising: acquiring data in a breast tomosynthesissystem; detecting patient motion from the acquired data; and identifyingto a user that motion was detected.
 47. The method of claim 46 includingstoring information indicative of patient motion.
 48. Apparatuscomprising: a breast tomosynthesis system which detects patient motionand selectively discards or mathematically corrects a portion ofprojection data during image reconstruction.
 49. A method comprising:improving image quality in a breast tomosynthesis system by detectingmotion and selectively discarding or mathematically correcting a portionof projection data during image reconstruction.
 50. The method of claim49 including storing information indicative of patient motion. 51.Apparatus comprising: a non-transitory computer-readable memory havingstored therein information indicative of patient motion associated withat least one image of a plurality of images of an imaging target from atime series during a scan.